Hi everyone!
Just sharing an update on my project Parax, which caters for "parametric modeling" in JAX.
Previously, Parax was more focused on scientific applications, however I've since generalized it to be a tool useful for any type of JAX work. It now has a strong focus on a clean, extandable API, as well as ensuring the library is entirely opt-in, as opposed to its previous versions which took a more framework-like approach.
Some of Parax's features:
- Derived/constrained parameters with metadata
- Computed PyTrees and callable parameterizations
- Abstract interfaces for fixed, bounded, and probabilistic PyTrees and parameters
- Filtering and manipulation tools
- Built-in wrapper for SciPy bounded optimization
The documentation is available here along with some basic examples. Perhaps the package is of use to someone out there!
Cheers,
Gary
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